完善目录结构
完善了目录结构，添加了以前的web段com组件调用的代码（在/测试目录下）（部署没有使用到）
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yanshui177
199
测试/单独功能测试/0-DLL测试（实际没有部署）/dll-goal无数据库/segmentation.cpp
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199
测试/单独功能测试/0-DLL测试（实际没有部署）/dll-goal无数据库/segmentation.cpp
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#pragma once
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#ifdef WIN32 //屏蔽VC6对STL的一些不完全支持造成
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#pragma warning (disable: 4514 4786)
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#endif
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#include <time.h>
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#include <ctime>
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#include <stdlib.h>
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#include <stdio.h>
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#include <iostream>
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#include <math.h>
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#include <cv.h>
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#include<io.h> //下面的5个用于读取文件夹下的所有文件名
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#include<vector>
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#include <string.h>
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#include<windows.h> //用于弹出提示框,,,切记！当调用<windows.h>时，不要调用MFC！（Afx.h)
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#include<string.h>
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using namespace std;
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int* binary(IplImage* img,int bithro); //二值化图像
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int outlinefeature(IplImage* imglk,int feature[ ][50]); //计算图像的轮廓特征值
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int read_scanf(const string &filename,const int &cols,vector<double *> &_vector); //读取已经存好的特征值
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IplImage* Cjbsb(IplImage* img,IplImage* imgjbsb,int jbwhite,int jbblack); //图像角标识别
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IplImage* outline(IplImage* imgbj); //计算图像对应的轮廓图
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IplImage* singlefeature(char* path,int feature[ ][50]); //得出单个文件的特征值
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char *fo = "H:\\logs_dll_check_only.txt";
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char rec[2000] = "\n结果集合为空:";
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FILE *fpzz3 = NULL;//需要注意
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extern "C" _declspec(dllexport) char * __stdcall WINAPI TEST(char *fpname1){
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return fpname1;//总文件夹的路径
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}
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extern "C" _declspec(dllexport) char * __stdcall WINAPI HWCV(char *fpname1,char *dest)
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{
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int conti = 1;
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int size, i, ii, jj, feature[50][50][30] = { 0 }, featureall;
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double featurep[50][50][30] = { 0 },bzcu[50][50] = { 0 }, bzckesa[50][50] = { 0 }, wcd[30] = { 0 };
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int featx[50][50] = { 0 }, featdif[30] = { 0 }, maxi; float maxx = 0; //最大特征值的标号与值
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int xyimgnum = 0; //嫌疑图片的数目
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char str[80]; //存储地址
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/*变量定义*/
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vector<string> suspict; //记录嫌疑图片地址
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vector<float> suspict_wcd;
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vector<string> files; //存储该生所有考试文件路径
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vector<string> dateVec, subjectVec, stuNum2;
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vector<int> flagVec;//记录查到的学生的所有考试信息
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files.push_back("D:\\tupian\\201110\\0534\\010209400748.jpg");
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files.push_back("D:\\tupian\\201010\\0665\\010209400748.jpg");
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files.push_back("D:\\tupian\\201606\\0668\\010209400748.jpg");
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files.push_back("D:\\tupian\\201101\\0799\\010209400748.jpg");
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files.push_back("D:\\tupian\\201101\\0883\\010209400748.jpg");
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files.push_back("D:\\tupian\\201201\\0884\\010209400748.jpg");
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files.push_back("D:\\tupian\\201107\\0885\\010209400748.jpg");
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files.push_back("D:\\tupian\\201307\\0886\\010209400748.jpg");
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files.push_back("D:\\tupian\\201307\\0887\\010209400748.jpg");
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files.push_back("D:\\tupian\\201107\\0888\\010209400748.jpg");
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files.push_back("D:\\tupian\\201404\\4685\\010209400748.jpg");
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files.push_back("D:\\tupian\\201104\\1180\\010209400748.jpg");
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files.push_back("D:\\tupian\\201110\\1181\\010209400748.jpg");
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files.push_back("D:\\tupian\\201510\\0359\\080215203444.jpg");
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files.push_back("D:\\tupian\\201212\\0101\\010209400748.jpg");
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files.push_back("D:\\tupian\\201606\\4927\\010209400748.jpg");
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size = files.size(); //图像的数目
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//开始对每一张图片进行处理
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for (i = 0; i < size; i++)
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{
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memset(str, 0, sizeof(str));
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memset(featx, 0, sizeof(featx));
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memset(bzcu, 0, sizeof(bzcu));
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strcpy(str, files[i].c_str());
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singlefeature(str, featx); //featx[][50]
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featureall = 0; //图像特征值和的初始化
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for (ii = 0; ii < 48; ii++) //将featx存起来,回头看能不能用函数换掉
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for (jj = ii + 1; jj < 47; jj++)
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{
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feature[ii][jj][i] = featx[ii][jj];
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featureall = featureall + featx[ii][jj];
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}
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//求轮廓方向特征featurep，式(5) 与标准差中的u的和
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for (ii = 0; ii < 48; ii++)
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for (jj = ii + 1; jj < 47; jj++)
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{
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featurep[ii][jj][i] = (double)featx[ii][jj] / featureall;
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bzcu[ii][jj] += (double)featx[ii][jj] / featureall * 1000; //标准差的值过小,进行放大（1）
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}
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}
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//处理完一个人的每一张图片后
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//----------------------------------------------------------//
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for (ii = 0; ii < 48; ii++)//求标准差中的u
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for (jj = ii + 1; jj < 47; jj++)
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bzcu[ii][jj] = bzcu[ii][jj] / size;
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/*将标准差中的kesa加载进来*/
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string bzcfile = "D:/Xiangmu/Img/bzc/bzc.txt";
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//txt文件中有47列
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int bzccolumns = 47;
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vector<double *> output_bzc;
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if (!read_scanf(bzcfile, bzccolumns, output_bzc)) return 0;
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//output_vector可视为二维数组;输出数组元素：
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//int rows=output_bzc.size();
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for (ii = 0; ii < 48; ii++)
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for (jj = ii + 1; jj < 47; jj++)
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bzckesa[ii][jj] = output_bzc[ii][jj];
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//求相似性就是带权卡方wcd
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for (i = 0; i < size; i++)
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for (ii = 0; ii < 48; ii++)
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for (jj = ii + 1; jj < 47; jj++)
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if (featurep[ii][jj][i] * featurep[ii][jj][conti] != 0 && bzckesa[ii][jj] != -1)
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wcd[i] += pow((featurep[ii][jj][i] - featurep[ii][jj][conti]), 2) / ((featurep[ii][jj][i] + featurep[ii][jj][conti])*bzckesa[ii][jj]);
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//求卡方距离的最大值
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for (i = 0; i < size; i++)
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{
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if (maxx < wcd[i]){ maxx = wcd[i]; maxi = i; }
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if (wcd[i] > 0.12)
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{
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xyimgnum++;
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suspict.push_back(files[i].c_str());
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suspict_wcd.push_back(wcd[i]);
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flagVec.push_back(1);//嫌疑标记
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}else
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{
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flagVec.push_back(0);
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}
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}
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/*存储文件记录*/
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//char* fpname = "C:/Users/闫帅帅/Desktop/result2.txt";
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//char record[2400] = { 0 };
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//FILE* fpzz = NULL;//需要注意
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fpzz3 = fopen(fo, "a"); //创建文件 //a
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if (NULL == fpzz3) return "ERR";//要返回错误代码
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fprintf(fpzz3, rec); //从控制台中读入并在文本输出
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fclose(fpzz3);
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fpzz3 = NULL;//需要指向空，否则会指向原打开文件地址
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//将结果存入txt
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memset(rec, 0, sizeof(rec));
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strcpy(rec, "图片总数为：");
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char pic_num[20];
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_itoa(size, pic_num, 10);
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strcat(rec, pic_num);
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if (xyimgnum > 0)
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{
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strcat(rec, "\n");
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for (i = 0; i < xyimgnum; i++)
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{
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strcat(rec, "\t");
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strcat(rec, suspict[i].c_str());
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strcat(rec, "\t");
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char a[20];
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sprintf(a, "%g", suspict_wcd[i]);
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strcat(rec, a);
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strcat(rec, "\n");
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}
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}
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else strcat(rec, "\t没有嫌疑图像！\n");
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fpzz3 = fopen(fo, "a"); //创建文件 //a
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if (NULL == fpzz3) return "ERR";//要返回错误代码
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fprintf(fpzz3, rec); //从控制台中读入并在文本输出
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fclose(fpzz3);
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fpzz3 = NULL;//需要指向空，否则会指向原打开文件地址
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suspict.clear();
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suspict_wcd.clear();
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output_bzc.clear();
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//memset(record, 0, 2400);
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memset(feature, 0, sizeof(feature));
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memset(featurep, 0, sizeof(featurep));
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memset(bzckesa, 0, sizeof(bzckesa));
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memset(wcd, 0, sizeof(wcd));
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memset(featdif, 0, sizeof(featdif));
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char out[100]="成功！\n";
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strcat(out, fpname1);
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sprintf(dest, out );
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return "return_OK";
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}
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